Time and Business Process Management: Problems, Achievements, Challenges (Invited Talk)

Authors Johann Eder , Marco Franceschetti



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Johann Eder
  • Department of Informatics Systems, Universität Klagenfurt, Austria
Marco Franceschetti
  • Department of Informatics Systems, Universität Klagenfurt, Austria

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Johann Eder and Marco Franceschetti. Time and Business Process Management: Problems, Achievements, Challenges (Invited Talk). In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 3:1-3:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.TIME.2020.3

Abstract

Processes have been successfully introduced for modeling dynamic phenomena in many areas like business, production, health care, etc. Many of these applications require to adequately deal with temporal aspects. Process models need to express temporal durations, temporal constraints like allowed time between events, and deadlines. For checking the correctness of process definitions with temporal constraints, different notions and algorithms have been developed. Schedules for the execution of processes can be computed and proactive time management supports process managers to avoid time failures during the execution of a process. We present an overview of the problems and the requirements for treating time in business processes and the solutions achieved by applying results and techniques of research in temporal representation and reasoning. We reflect where expectations have not yet been met and sketch challenges in temporal representation and reasoning for addressing advanced requirements of the management of business processes.

Subject Classification

ACM Subject Classification
  • Information systems → Process control systems
  • Applied computing → Business process management
  • Information systems → Temporal data
Keywords
  • Business Process management
  • Temporal constraints
  • Scheduling
  • Process Evolution
  • Probabilistic Controllability

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